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The modulation of protein function via designed small molecules is providing new opportunities in chemical biology and medicinal chemistry. While drugs have traditionally been developed to block enzymatic activities through active site occupation, a growing number of strategies now aim to control protein functions in an allosteric fashion, allowing for the tuning of a target’s activation or deactivation via the modulation of the populations of conformational ensembles that underlie its function. In the context of the discovery of new active leads, it would be very useful to generate hypotheses for the functional impact of new ligands. Since the discovery and design of allosteric modulators (inhibitors/activators) is still a challenging and often serendipitous target, the development of a rapid and robust approach to predict the functional profile of a new ligand would significantly speed up candidate selection. Herein, we present different machine learning (ML) classifiers to distinguish between potential orthosteric and allosteric binders. Our approach integrates information on the chemical fingerprints of the ligands with descriptors that recapitulate ligand effects on protein functional motions. The latter are derived from molecular dynamics (MD) simulations of the target protein in complex with orthosteric or allosteric ligands. In this framework, we train and test different ML architectures, which are initially probed on the classification of orthosteric versus allosteric ligands for cyclin-dependent kinases (CDKs). The results demonstrate that different ML methods can successfully partition allosteric versus orthosteric effectors (although to different degrees). Next, we further test the models with FDA-approved CDK drugs, not included in the original dataset, as well as ligands that target other kinases, to test the range of applicability of these models outside of the domain on which they were developed. Overall, the results show that enriching the training dataset with chemical physics-based information on the protein–ligand dynamic cross-talk can significantly expand the reach and applicability of approaches for the prediction and classification of the mode of action of small molecules.

L’utilizzo degli integratori è largamente diffuso in occidente e in Italia troviamo il mercato più ampio, con una previsione di vendite di 5 miliardi di euro nel 2025. Le motivazioni all’acquisto sono principalmente la ricerca del benessere psico-fisico o la risposta a specifiche esigenze di salute. Gli integratori sono prodotti destinati a integrare la dieta e fornire sostanze nutritive che mancano o non sono assunte in quantità sufficienti con la sola alimentazione. Tuttavia, il concetto di integrazione è stato esteso a sostanze di cui non abbiamo un reale fabbisogno in condizioni fisiologiche e a dosaggi non più di integrazione, ma farmacologici, causando confusione tra gli operatori e i consumatori. Gli integratori, se usati senza controllo, possono comportare rischi per la salute. In particolare, la potenziale tossicità dei nutrienti e degli integratori è un concetto spesso dimenticato, nonostante nei Livelli di Assunzione di Riferimento di Nutrienti (LARN) per la popolazione italiana sia definito per ogni nutriente il livello massimo tollerabile di assunzione. La scarsità di studi sistematici sugli effetti avversi degli integratori, che possono essere immessi sul mercato senza il supporto di studi clinici, rende difficile stabilire un nesso causale tra l’assunzione di un integratore e l’insorgenza di sintomi avversi. La tossicità è rara per le vitamine idrosolubili, ma più frequenti per le vitamine liposolubili, come la vitamina E, la vitamina A e i carotenoidi, e la vitamina D. In determinate situazioni, alcune categorie di persone possono essere a rischio di carenze nutrizionali; tuttavia, l’integrazione di nutrienti deve seguire in ogni caso un percorso di valutazione dello stato di nutrizione e di modulazione del comportamento alimentare e va mantenuta per il tempo necessario al recupero di un corretto stato nutrizionale e comportamentale. L’uso di integratori può anche predisporre gli individui a comportamenti alimentari scorretti e deve essere attentamente valutato in base al reale rapporto costo-beneficio.

The article is a review of existing studies that explores the link between eating disorders and oral health issues. It found that people with eating disorders, including anorexia nervosa and bulimia nervosa, may experience dental problems such as tooth erosion, cavities, and altered saliva production. The review findings emphasize the importance of dental care providers recognizing these signs early and suggests better training for dental professionals. By doing so, they can help diagnose eating disorders sooner and recommend appropriate treatment. This approach aims to improve patients’ overall wellbeing by addressing both the oral health issues and the underlying eating disorders, making it essential for patients and medical teams to be aware of the interconnectedness between oral health and eating disorders.

Negli ultimi anni il digiuno intermittente è emerso quale approccio innovativo per promuovere il calo ponderale e migliorare lo stato di salute metabolica in contrapposizione agli interventi più convenzionali incentrati sulla restrizione calorica. Il digiuno intermittente (Intermittent Fasting) e il Time-Restricted Feeding(TRF) negli animali (anche noto come Time-Restricted Eating, TRE nell’uomo) hanno raggiunto una crescente popolarità parallelamente al consistente aumento delle evidenze scientifiche nell’ambito della cronobiologia, con la recente attribuzione del premio Nobel per la Medicina nel 2017 a Jeffrey C. Hall, Michael Rosbash e Michael W. Young quale riconoscimento per il contributo alle scoperte dei meccanismi molecolari che sottendono il ritmo circadiano. Il sistema circadiano regola il metabolismo in un ciclo di circa ventiquattro ore, determinando una ritmicità circadiana endogena nel dispendio energetico, nell’appetito, nella sensibilità insulinica e in altri processi metabolici. Molti di tali processi, tra cui la sensibilità insulinica e la termogenesi indotta dalla dieta, presentano un picco nella prima parte della giornata. Numerose evidenze sia nell’animale sia nell’uomo sottolineano che alimentarsi in momenti della giornata che siano asincroni rispetto ai ritmi delle suddette funzioni metaboliche promuova l’eccesso ponderale e le alterazioni metaboliche ad esso associate.

Descritte per la prima volta negli anni’20 del Novecento, le diete chetogeniche sono passate da dietoterapia “di nicchia” per epilessie farmaco-resistenti o secondarie a rare malattie metaboliche (es. deficit di GLUT-1), a trattamento diffuso di patologie associate a malnutrizione per eccesso (diabete mellito di tipo 2, obesità). Attualmente non esiste una definizione univoca, ma si possono individuare tre classificazioni che combinano elementi differenti (composizione in macronutrienti, bilancio energetico, rapporto chetogenico) e risultano, pertanto, tra loro complementari. L’eterogeneità nella nomenclatura ha contribuito a generare false convinzioni sulla dieta chetogena, talvolta accostata a protocolli “low-carb” o “iperproteici”. Fare chiarezza non rappresenta quindi un mero esercizio accademico, ma un imperativo sia della ricerca sia della pratica clinica.

The SARS-CoV-2 spike (S) protein is exposed on the viral surface and is the first point of contact between the virus and the host. For these reasons it represents the prime target for Covid-19 vaccines. In recent months, variants of this protein have started to emerge. Their ability to reduce or evade recognition by S-targeting antibodies poses a threat to immunological treatments and raises concerns for their consequences on vaccine efficacy. To develop a model able to predict the potential impact of S-protein mutations on antibody binding sites, we performed unbiased multi-microsecond molecular dynamics of several glycosylated S-protein variants and applied a straightforward structure-dynamics-energy based strategy to predict potential changes in immunogenic regions on each variant. We recover known epitopes on the reference D614G sequence. By comparing our results, obtained on isolated S-proteins in solution, to recently published data on antibody binding and reactivity in new S variants, we directly show that modifications in the S-protein consistently translate into the loss of potentially immunoreactive regions. Our findings can thus be qualitatively reconnected to the experimentally characterized decreased ability of some of the Abs elicited against the dominant S-sequence to recognize variants. While based on the study of SARS-CoV-2 spike variants, our computational epitope-prediction strategy is portable and could be applied to study immunoreactivity in mutants of proteins of interest whose structures have been characterized, helping the development/selection of vaccines and antibodies able to control emerging variants.

The disruptive impact of the COVID-19 pandemic has led the scientific community to undertake an unprecedented effort to characterize viral infection mechanisms. Among these, interactions between the viral glycosylated Spike and the human receptors ACE2 and TMPRSS2 are key to allowing virus invasion. Here, we report and test a fully rational methodology to design molecules that are capable of perturbing the interactions between these critical players in SARS-CoV-2 pathogenicity. To this end, we computationally identify substructures on the fully glycosylated Spike protein that are not intramolecularly optimized and are thus prone to being stabilized by forming complexes with ACE2 and TMPRSS2. With the aim of competing with the Spike-mediated cell entry mechanisms, we have engineered the predicted putative interaction regions in the form of peptide mimics that could compete with Spike for interaction with ACE2 and/or TMPRSS2. Experimental models of viral entry demonstrate that the designed molecules are able to interfere with viral entry into ACE2/TMPRSS2 expressing cells, while they have no effects on the entry of control viral particles that do not harbor the Spike protein or on the entry of Spike-presenting viral particles into cells that do not display its receptors on their surface.

Purpose: The aim of the study was to examine the effects of meal supervision, provided by health professionals, volunteers or family members, on anthropometric, nutritional, psychological, and behavioural outcomes in patients with eating disorders (EDs). Methods: The present systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The last search was conducted in three databases (PubMed, Scopus, and the Cochrane library). Inclusion criteria considered paediatric and adult patients suffering from EDs, regardless of ethnicity, and treated in different therapeutic settings. The quality of the studies was evaluated using the Newcastle Ottawa Scale (NOS) adapted for cross-sectional studies and Version 2 of the Cochrane risk-of-bias assessment tool for randomised trials. Results: 3282 articles were retrieved, out of which only 6 met the eligibility criteria. A marked heterogeneity in definitions and approaches to supervised mealtime was observed. This variability emerged in the methodologies used in the supervised meal, and in the reference values for the outcome measures that were used, such as the analysis of different parameters. Level of evidence: Level IV systematic reviews of uncontrolled trials.

Raman spectroscopy is largely informative about organic matter (OM) chemical composition and structure and can therefore be applied to evaluate the thermal maturity of coals, carbonaceous materials and kerogens, i.e., their degree of evolution during burial heating. The evaluation of OM maturity is commonly performed by band-fitting followed by the measure of suitable spectral parameters (typically band separations and area ratios). However, this procedure can introduce some subjectivity both in the number and line-shape of the fitting bands and in the definition and selection of the most meaningful spectroscopic parameters. Here, a principal component analysis–partial least squares regression (PCA–PLS) chemometric approach for the treatment of spectra is presented, that is intrinsically unaffected by such arbitrariness. In fact, the total spectrum is analyzed in order to extract the spectroscopic ranges of maximum variance in a multivariate approach. In addition, being automated, the treatment is well-suited to huge sets, as those commonly collected to appropriately and reliably evaluate the chemical–physical and geological variables in an exploration well. As a case study the maturity profile (maximum paleotemperature) of OM from a well drilled in the Lower Congo basin (offshore Angola) is evaluated, both by spectral parameters and by PCA–PLS analysis, with results in good agreement on the basis of the prediction error. A set of coals is adopted as a reference to predict the reflectance in oil (%Ro) profile from the Raman data. The comparison of the calculated %Rovalues with the experimental ones, presenting, in this case, some suppressed values, shows that the Raman analysis is not affected by underestimation of maturity as the vitrinite reflectance may be.

SARS-CoV-2 has evolved rapidly in the first 3 years of pandemic diffusion. The initial evolution of the virus appeared to proceed through big jumps in sequence changes rather than through the stepwise accumulation of point mutations on already established variants. Here, we examine whether this nonlinear mutational process reverberates in variations of the conformational dynamics of the SARS-CoV-2 Spike protein (S-protein), the first point of contact between the virus and the human host. We run extensive microsecond-scale molecular dynamics simulations of seven distinct variants of the protein in their fully glycosylated state and set out to elucidate possible links between the mutational spectrum of the S-protein and the structural dynamics of the respective variant, at global and local levels. The results reveal that mutation-dependent structural and dynamic modulations mostly consist of increased coordinated motions in variants that acquire stability and in an increased internal flexibility in variants that are less stable. Importantly, a limited number of functionally important substructures (the receptor binding domain, in particular) share the same time of movements in all variants, indicating efficient preorganization for functional regions dedicated to host interactions. Our results support a model in which the internal dynamics of the S-proteins from different strains varies in a way that reflects the observed random and non-stepwise jumps in sequence evolution, while conserving the functionally oriented traits of conformational dynamics necessary to support productive interactions with host receptors.

Severe sleep disruption is a well-documented problem in mechanically ventilated, critically ill patients during their time in the intensive care unit (ICU), but little attention has been paid to the period when these patients become clinically stable and are transferred to a step-down unit (SDU). We monitored the 24-h sleep pattern in 2 groups of patients, one on mechanical ventilation and the other breathing spontaneously, admitted to our SDU to assess the presence of sleep abnormalities and their association with mechanical ventilation.